A Hybrid Programming Model for Optimal Production Planning under Demand Uncertainty in Refinery

›› 2008, Vol. 16 ›› Issue (2): 241-246.

A Hybrid Programming Model for Optimal Production Planning under Demand Uncertainty in Refinery

李初福¹, 何小荣¹, 陈丙珍¹, 徐强², 刘朝玮²

1. Department of Chemical Engineering, Tsinghua University, Beijing 100084, China;
2. Department of Chemical Engineering, Lamar University, Beaumont 77710, USA

收稿日期:2007-05-08 修回日期:2007-09-20 出版日期:2008-04-28 发布日期:2008-04-28
通讯作者: HE Xiaorong,E-mail:hexr@tsinghua.edu.cn
基金资助:
the Specialized Research Fund for Doctoral Program of Higher Education of China(20060003087)

A Hybrid Programming Model for Optimal Production Planning under Demand Uncertainty in Refinery

LI Chufu¹, HE Xiaorong¹, CHEN Bingzhen¹, XU Qiang², LIU Chaowei²

1. Department of Chemical Engineering, Tsinghua University, Beijing 100084, China;
2. Department of Chemical Engineering, Lamar University, Beaumont 77710, USA

Received:2007-05-08 Revised:2007-09-20 Online:2008-04-28 Published:2008-04-28
Supported by:
the Specialized Research Fund for Doctoral Program of Higher Education of China(20060003087)

摘要/Abstract

摘要： Production planning under uncertainty is considered as one of the most important problems in plant-wide optimization.In this article,first,a stochastic programming model with uniform distribution assumption is developed for refinery production planning under demand uncertainty,and then a hybrid programming model incorporating the linear programming model with the stochastic programming one by a weight factor is proposed. Subsequently,piecewise linear approximation functions are derived and applied to solve the hybrid programming model under uniform distribution assumption.Case studies show that the linear approximation algorithm is effective to solve the hybrid programming model,along with an error≤0.5% when the deviation/mean≤20%.The simulation results indicate that the hybrid programming model with an appropriate weight factor(0.1-0.2)can effectively improve the optimal operational strategies under demand uncertainty,achieving higher profit than the lin-ear programming model and the stochastic programming one with about 1.5% and 0.4% enhancement,respectively.

关键词: production planning, demand uncertainty, stochastic programming, linear programming, hybrid pro-gramming

Abstract: Production planning under uncertainty is considered as one of the most important problems in plant-wide optimization.In this article,first,a stochastic programming model with uniform distribution assumption is developed for refinery production planning under demand uncertainty,and then a hybrid programming model incorporating the linear programming model with the stochastic programming one by a weight factor is proposed. Subsequently,piecewise linear approximation functions are derived and applied to solve the hybrid programming model under uniform distribution assumption.Case studies show that the linear approximation algorithm is effective to solve the hybrid programming model,along with an error≤0.5% when the deviation/mean≤20%.The simulation results indicate that the hybrid programming model with an appropriate weight factor(0.1-0.2)can effectively improve the optimal operational strategies under demand uncertainty,achieving higher profit than the lin-ear programming model and the stochastic programming one with about 1.5% and 0.4% enhancement,respectively.

Key words: production planning, demand uncertainty, stochastic programming, linear programming, hybrid pro-gramming

李初福, 何小荣, 陈丙珍, 徐强, 刘朝玮. A Hybrid Programming Model for Optimal Production Planning under Demand Uncertainty in Refinery[J]. , 2008, 16(2): 241-246.

LI Chufu, HE Xiaorong, CHEN Bingzhen, XU Qiang, LIU Chaowei. A Hybrid Programming Model for Optimal Production Planning under Demand Uncertainty in Refinery[J]. , 2008, 16(2): 241-246.

参考文献

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A Hybrid Programming Model for Optimal Production Planning under Demand Uncertainty in Refinery

A Hybrid Programming Model for Optimal Production Planning under Demand Uncertainty in Refinery

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